Circulating Unmethylated Insulin DNA As a Biomarker of Human Beta Cell Death: A Multi-laboratory Assay Comparison

Prediction of progression to type 1 diabetes with dynamic biomarkers and risk scores

Identifying biomarkers of functional β-cell loss is an important step in the risk stratification of type 1 diabetes. Genetic risk scores (GRS), generated by profiling an array of single nucleotide polymorphisms, are a widely used type 1 diabetes risk-prediction tool. Type 1 diabetes screening studies have relied on a combination of biochemical (autoantibody) and GRS screening methodologies for identifying individuals at high-risk of type 1 diabetes. A limitation of these screening tools is that the presence of autoantibodies marks the initiation of β-cell loss, and is therefore not the best biomarker of progression to early-stage type 1 diabetes. GRS, on the other hand, represents a static biomarker offering a single risk score over an individual's lifetime. In this Personal View, we explore the challenges and opportunities of static and dynamic biomarkers in the prediction of progression to type 1 diabetes. We discuss future directions wherein newer dynamic risk scores could be used to predict type 1 diabetes risk, assess the efficacy of new and emerging drugs to retard, or prevent type 1 diabetes, and possibly replace or further enhance the predictive ability offered by static biomarkers, such as GRS.

Association of DNA Methylation with Infant Birth Weight in Women with Gestational Diabetes

Offspring exposed to gestational diabetes mellitus (GDM) exhibit greater adiposity at birth. This early-life phenotype may increase offspring risk of developing obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease later in life. Infants born to women with GDM have a dysregulation of several hormones, cytokines, and growth factors related to fetal fat mass growth. One of the molecular mechanisms of GDM influencing these factors is epigenetic alterations, such as DNA methylation (DNAm). This review will examine the role of DNAm as a potential biomarker for monitoring fetal growth during pregnancy in women with GDM. This information is relevant since it may provide useful new biomarkers for the diagnosis, prognosis, and treatment of fetal growth and its later-life health consequences.

The pathogenic "symphony" in type 1 diabetes: A disorder of the immune system, β cells, and exocrine pancreas

Type 1 diabetes (T1D) is widely considered to result from the autoimmune destruction of insulin-producing β cells. This concept has been a central tenet for decades of attempts seeking to decipher the disorder's pathogenesis and prevent/reverse the disease. Recently, this and many other disease-related notions have come under increasing question, particularly given knowledge gained from analyses of human T1D pancreas. Perhaps most crucial are findings suggesting that a collective of cellular constituents-immune, endocrine, and exocrine in origin-mechanistically coalesce to facilitate T1D. This review considers these emerging concepts, from basic science to clinical research, and identifies several key remaining knowledge voids.

Higher β cell death in pregnant women, measured by DNA methylation patterns of cell-free DNA, compared to new-onset type 1 and type 2 diabetes subjects: a cross-sectional study

Diabetes is a metabolic disorder of glucose homeostasis in which β cell destruction occurs silently and is detected mainly when symptoms appear. In the last few years, it has emerged a great interest in developing markers capable of detecting pancreatic β cell death focused on improving early diagnosis and getting a better treatment response, mainly in type 1 diabetes. But other types of diabetes would also benefit from early detection of β cell death. Differentially methylated circulating DNA is being studied as minimally invasive biomarker of cell death. We aimed to explore whether the unmethylated/methylated ratio of the insulin and amylin genes might be a good biomarker of β cell death in different types of diabetes. A lower index ∆Ct indicates a higher rate of β-cell death. Plasma samples from subjects without diabetes, pregnant women, pregnant with gestational diabetes (GDM), type 1 diabetes and type 2 diabetes were analyzed. A qPCR reaction with specific primers for both methylated and unmethylated fragments of insulin and amylin genes were carried out. Pregnant women, GDM and non- GDM, showed a higher β-cell death for both markers (∆INS = 3.8 ± 2.1 and ∆Amylin = 8.5 ± 3.6), whereas T1D presented lower rate (∆INS = 6.2 ± 2.1 and ∆Amylin = 10.7 ± 2.9) comparable to healthy subjects. The insulin methylation index was associated with the newborn birth weight (r = 0.46; p = 0.033) and with insulin resistance (r = -0.533; p = 0.027) in the GDM group. The higher rate of β-cell death was observed in pregnant women independently of their metabolic status. These indexes could be a good indicator of β cell death in processes caused by defects on insulin secretion, insulin action, or both.

Adipose cell-free DNA in diabetes

Cancer-associated necrosis is a well-known source of cell-free DNA (cfDNA). However, the origins of cfDNA are not strictly limited to cancer. Additionally, dietary exposure induces apoptosis-induced proliferation in adipocytes, leading to the release of cfDNA. The genetic information derived from cfDNA as a result of apoptosis-induced proliferation contains specific methylation patterns in adipose tissue that can be used as a marker to detect the risk of developing Type 2 diabetes Mellitus (T2DM) in the future. cfDNA is superior to peripheral blood leukocytes (PBL) and whole blood samples for reflecting tissue pathology due to the frequent use of PBL and whole blood samples that do not match tissue pathology. The difficulty of demonstrating that cfDNA is derived from adipose tissue. We propose several promising techniques by analyzing cfDNA derived from adipose tissue to detect T2DM risk. First, adipose-specific genes such as ADIPOQ and Leptin were utilized. Second, MCTA-Seq, EpiSCORE, deconvolution, multiplexing, and automated machine learning (AutoML) were used to determine the proportion of total methylation in related genes.

Novel method utilizing bisulfite conversion with dual amplification-refractory mutation system polymerase chain reaction to detect circulating pancreatic β-cell cfDNA

Aims/Introduction

Several research groups have reported methods for quantifying pancreatic beta cell (β‐cell) injury by measuring β‐cell‐specific CpG unmethylation of the insulin gene in circulation using digital droplet PCR or next‐generation sequencing. However, these methods have certain disadvantages, such as the need to consider the background signal owing to the small number of target CpG sites and the need for unique equipment.

Materials and Methods

We established a novel method for detecting four CpG unmethylations of the insulin gene using two‐step amplification refractory mutation system PCR. We applied it to type 1 diabetes (T1D) patients with a wide range of disease durations and to healthy adults.

Results

The assay showed high linearity and could detect a single copy of unmethylated insulin DNA in experiments using methylated and unmethylated plasmid DNA. The unmethylated insulin DNA level in the type 1 diabetes group, whose β‐cell mass was considerably reduced, was similar to that of healthy adults. An inverse correlation was observed between copy number and disease duration in patients with unmethylated insulin DNA‐positive type 1 diabetes.

Conclusions

We developed a novel method for detecting unmethylated insulin DNA in circulation that can be performed using a conventional real‐time PCR system. This method would be useful for analyzing dynamic profiles of β‐cells in human disease such as type 1 diabetes.

Quantification of Unmethylated Insulin DNA Using Methylation Sensitive Restriction Enzyme Digital Polymerase Chain Reaction

Assessment of specific β-cell death can be used to determine the quality and viability of pancreatic islets prior to transplantation and hence predict the suitability of the pancreas for isolation. Recently, several groups have demonstrated that unmethylated insulin (INS)-DNA is correlated to β-cell death in type 1 diabetes patients and during clinical islet isolation and subsequent transplantation. Here, we present a step-by-step protocol of our novel developed method for quantification of the relative amount of unmethylated INS-DNA using methylation sensitive restriction enzyme digital polymerase chain reaction This method provides a novel and sensitive way to quantify the relative amount of β-cell derived unmethylated INS-DNA in cellular lysate. We therefore suggest that this technique can be of value to reliably determine the purity of an islet preparation and may also serve as a measure of the quality of islets prior to transplantation measuring unmethylated INS-DNA as a reflection of the relative amount of lysed β-cells.

Personalized Immunotherapies for Type 1 Diabetes: Who, What, When, and How?

Our understanding of the immunopathological features of type 1 diabetes (T1D) has greatly improved over the past two decades and has shed light on disease heterogeneity dictated by multiple immune, metabolic, and clinical parameters. This may explain the limited effects of immunotherapies tested so far to durably revert or prevent T1D, for which life-long insulin replacement remains the only therapeutic option. In the era of omics and precision medicine, offering personalized treatment could contribute to turning this tide. Here, we discuss how to structure the selection of the right patient at the right time for the right treatment. This individualized therapeutic approach involves enrolling patients at a defined disease stage depending on the target and mode of action of the selected drug, and better stratifying patients based on their T1D endotype, reflecting intrinsic disease aggressiveness and immune context. To this end, biomarker screening will be critical, not only to help stratify patients and disease stage, but also to select the best predicted responders ahead of treatment and at early time points during clinical trials. This strategy could contribute to increase therapeutic efficacy, notably through the selection of drugs with complementary effects, and to further develop precision multi-hit medicine.

Living Dangerously: Protective and Harmful ER Stress Responses in Pancreatic β-Cells

Type 2 diabetes (T2D) is a growing cause of poor health, psychosocial burden, and economic costs worldwide. The pancreatic β-cell is a cornerstone of metabolic physiology. Insulin deficiency leads to hyperglycemia, which was fatal before the availability of therapeutic insulins; even partial deficiency of insulin leads to diabetes in the context of insulin resistance. Comprising only an estimated 1 g or <1/500th of a percent of the human body mass, pancreatic β-cells of the islets of Langerhans are a vulnerable link in metabolism. Proinsulin production constitutes a major load on β-cell endoplasmic reticulum (ER), and decompensated ER stress is a cause of β-cell failure and loss in both type 1 diabetes (T1D) and T2D. The unfolded protein response (UPR), the principal ER stress response system, is critical for maintenance of β-cell health. Successful UPR guides expansion of ER protein folding capacity and increased β-cell number through survival pathways and cell replication. However, in some cases the ER stress response can cause collateral β-cell damage and may even contribute to diabetes pathogenesis. Here we review the known beneficial and harmful effects of UPR pathways in pancreatic β-cells. Improved understanding of this stress response tipping point may lead to approaches to maintain β-cell health and function.

ITGB4 as a novel serum diagnosis biomarker and potential therapeutic target for colorectal cancer

Purpose

To develop new and effective biomarkers for the diagnosis of colorectal cancer (CRC).

Experimental design

The serum expression of ITGB4 (49 CRC and 367 HC) was detected by enzyme‐linked immunosorbent assay (ELISA), and its diagnostic value was analyzed using the receiver operating characteristic (ROC) curve. The sensitivity and specificity of ITGB4 in CRC diagnosis were calculated through statistical analysis. The optimal clinical cutoff value was calculated using the Youden index, and diagnostic efficacy was analyzed in a larger serum sample (98 CRC and 1631 non‐CRC). The expression of ITGB4 was measured by CyTOF (cell experimental technology) at the single‐cell level, and characteristics were analyzed using viSNE and SPADE TREE.

Results

Serum ITGB4 and CEA levels were significantly higher in CRC patients than in HC and non‐CRC patients. The use of serum ITGB4 levels for the diagnosis of CRC has a high sensitivity (79%) but not high specificity when the clinical cutoff value was 0.70 ng/mL. However, the optimal cutoff value was 1.6 ng/mL with 86.2% specificity and 52.0% sensitivity, and the diagnostic efficacy was greatly improved with high specificity (82.0%) and sensitivity (71.4%) when combined with CEA. ITGB4 expression characteristics were measured and related to the expression of EpCAM, Ck8/18, and perforin at the single‐cell level. Single‐cell analysis showed that cell clusters with low expression of CK8/18 and ITGB4 were more sensitive to 5FU and radiotherapy (RT).

Conclusions

ITGB4 is an effective diagnostic serum biomarker and a potential therapeutic target for CRC.

Tutorial: best practices and considerations for mass-spectrometry-based protein biomarker discovery and validation

Mass-spectrometry-based proteomic analysis is a powerful approach for discovering new disease biomarkers. However, certain critical steps of study design such as cohort selection, evaluation of statistical power, sample blinding and randomization, and sample/data quality control are often neglected or underappreciated during experimental design and execution. This tutorial discusses important steps for designing and implementing a liquid-chromatography-mass-spectrometry-based biomarker discovery study. We describe the rationale, considerations and possible failures in each step of such studies, including experimental design, sample collection and processing, and data collection. We also provide guidance for major steps of data processing and final statistical analysis for meaningful biological interpretations along with highlights of several successful biomarker studies. The provided guidelines from study design to implementation to data interpretation serve as a reference for improving rigor and reproducibility of biomarker development studies.

Immunotherapy: Building a bridge to a cure for type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disease in which T cells attack and destroy the insulin-producing β cells in the pancreatic islets. Genetic and environmental factors increase T1D risk by compromising immune homeostasis. Although the discovery and use of insulin have transformed T1D treatment, insulin therapy does not change the underlying disease or fully prevent complications. Over the past two decades, research has identified multiple immune cell types and soluble factors that destroy insulin-producing β cells. These insights into disease pathogenesis have enabled the development of therapies to prevent and modify T1D. In this review, we highlight the key events that initiate and sustain pancreatic islet inflammation in T1D, the current state of the immunological therapies, and their advantages for the treatment of T1D.

The MicroRNA Landscape of Acute Beta Cell Destruction in Type 1 Diabetic Recipients of Intraportal Islet Grafts

Ongoing beta cell death in type 1 diabetes (T1D) can be detected using biomarkers selectively discharged by dying beta cells into plasma. microRNA-375 (miR-375) ranks among the top biomarkers based on studies in animal models and human islet transplantation. Our objective was to identify additional microRNAs that are co-released with miR-375 proportionate to the amount of beta cell destruction. RT-PCR profiling of 733 microRNAs in a discovery cohort of T1D patients 1 h before/after islet transplantation indicated increased plasma levels of 22 microRNAs. Sub-selection for beta cell selectivity resulted in 15 microRNAs that were subjected to double-blinded multicenter analysis. This led to the identification of eight microRNAs that were consistently increased during early graft destruction: besides miR-375, these included miR-132/204/410/200a/429/125b, microRNAs with known function and enrichment in beta cells. Their potential clinical translation was investigated in a third independent cohort of 46 transplant patients by correlating post-transplant microRNA levels to C-peptide levels 2 months later. Only miR-375 and miR-132 had prognostic potential for graft outcome, and none of the newly identified microRNAs outperformed miR-375 in multiple regression. In conclusion, this study reveals multiple beta cell-enriched microRNAs that are co-released with miR-375 and can be used as complementary biomarkers of beta cell death.

Cell-Free DNA Fragments as Biomarkers of Islet β-Cell Death in Obesity and Type 2 Diabetes

Type 2 diabetes (T2D) typically occurs in the setting of obesity and insulin resistance, where hyperglycemia is associated with decreased pancreatic β-cell mass and function. Loss of β-cell mass has variably been attributed to β-cell dedifferentiation and/or death. In recent years, it has been proposed that circulating epigenetically modified DNA fragments arising from β cells might be able to report on the potential occurrence of β-cell death in diabetes. Here, we review published literature of DNA-based β-cell death biomarkers that have been evaluated in human cohorts of islet transplantation, type 1 diabetes, and obesity and type 2 diabetes. In addition, we provide new data on the applicability of one of these biomarkers (cell free unmethylated INS DNA) in adult cohorts across a spectrum from obesity to T2D, in which no significant differences were observed, and compare these findings to those previously published in youth cohorts where differences were observed. Our analysis of the literature and our own data suggest that β-cell death may occur in subsets of individuals with obesity and T2D, however a more sensitive method or refined study designs are needed to provide better alignment of sampling with disease progression events.

Circulating Free DNA and Its Emerging Role in Autoimmune Diseases

Liquid biopsies can be used to analyse tissue-derived information, including cell-free DNA (cfDNA), circulating rare cells, and circulating extracellular vesicles in the blood or other bodily fluids, representing a new way to guide therapeutic decisions in cancer. Among the new challenges of liquid biopsy, we found clinical application in nontumour pathologies, including autoimmune diseases. Since the discovery of the presence of high levels of cfDNA in patients with systemic lupus erythaematosus (SLE) in the 1960s, cfDNA research in autoimmune diseases has mainly focused on the overall quantification of cfDNA and its association with disease activity. However, with technological advancements and the increasing understanding of the role of DNA sensing receptors in inflammation and autoimmunity, interest in cfDNA and autoimmune diseases has not expanded until recently. In this review, we provide an overview of the basic biology of cfDNA in the context of autoimmune diseases as a biomarker of disease activity, progression, and prediction of the treatment response. We discuss and integrate available information about these important aspects.

The role of beta-cell dysfunction in early type 1 diabetes

PURPOSE OF REVIEW

Emerging data have suggested that β-cell dysfunction may exacerbate the development and progression of type 1 diabetes (T1D). In this review, we highlight clinical and preclinical studies suggesting a role for β-cell dysfunction during the evolution of T1D and suggest agents that may promote β-cell health in T1D.

RECENT FINDINGS

Metabolic abnormalities exist years before development of hyperglycemia and exhibit a reproducible pattern reflecting progressive deterioration of β-cell function and increases in β-cell stress and death. Preclinical studies indicate that T1D may be prevented by modification of pathways impacting intrinsic β-cell stress and antigen presentation. Recent findings suggest that differences in metabolic phenotypes and β-cell stress may reflect differing endotypes of T1D. Multiple pathways representing potential drug targets have been identified, but most remain to be tested in human populations with preclinical disease.

SUMMARY

This cumulative body of work shows clear evidence that β-cell stress, dysfunction, and death are harbingers of impending T1D and likely contribute to progression of disease and insulin deficiency. Treatment with agents targeting β-cell health could augment interventions with immunomodulatory therapies but will need to be tested in intervention studies with endpoints carefully designed to capture changes in β-cell function and health.

C-Peptide Levels in Subjects Followed Longitudinally Before and After Type 1 Diabetes Diagnosis in TrialNet

OBJECTIVE

Insulin secretion declines rapidly after diagnosis of type 1 diabetes, followed by a slower rate of change. Previous studies have demonstrated that the C-peptide decline begins before the clinical diagnosis. Changes in insulin secretion in the same individuals studied from preclinical stages through and after clinical diagnosis have not been previously reported.

RESEARCH DESIGN AND METHODS

Antibody-positive relatives undergo sequential oral glucose tolerance testing (OGTT) as part of TrialNet's Pathway to Prevention study and continue both OGTT and mixed-meal tolerance testing (MMTT) as part of the Long-term Investigational Follow-up in TrialNet study if they develop type 1 diabetes. We analyzed glucose and C-peptide data obtained from 80 TrialNet subjects who had OGTT before and after clinical diagnosis. Separately, we compared C-peptide response to OGTT and MMTT in 127 participants after diagnosis.

RESULTS

C-peptide did not change significantly until 6 months before the clinical diagnosis of type 1 diabetes and continued to decline postdiagnosis, and the rates of decline for the first 6 months postdiagnosis were similar to the 6 months prediagnosis. There were no significant differences in MMTT and OGTT C-peptide responses in paired tests postdiagnosis.

CONCLUSIONS

This is the first analysis of C-peptide levels in longitudinally monitored patients with type 1 diabetes studied from before diagnosis and continuing to the postdiagnosis period. These data highlight the discordant timing between accelerated β-cell dysfunction and the current glucose thresholds for clinical diagnosis. To preserve β-cell function, disease-modifying therapy should start at or before the acute decline in C-peptide.